Search Shortcut cmd + k | ctrl + k
- Installation
- Documentation
- Getting Started
- Connect
- Data Import
- Overview
- Data Sources
- CSV Files
- JSON Files
- Overview
- Creating JSON
- Loading JSON
- Writing JSON
- JSON Type
- JSON Functions
- Format Settings
- Installing and Loading
- SQL to / from JSON
- Caveats
- Multiple Files
- Parquet Files
- Partitioning
- Appender
- INSERT Statements
- Client APIs
- Overview
- ADBC
- C
- Overview
- Startup
- Configuration
- Query
- Data Chunks
- Vectors
- Values
- Types
- Prepared Statements
- Appender
- Table Functions
- Replacement Scans
- API Reference
- C++
- CLI
- Overview
- Arguments
- Dot Commands
- Output Formats
- Editing
- Safe Mode
- Autocomplete
- Syntax Highlighting
- Known Issues
- Dart
- Go
- Java (JDBC)
- Julia
- Node.js (Deprecated)
- Node.js (Neo)
- ODBC
- PHP
- Python
- Overview
- Data Ingestion
- Conversion between DuckDB and Python
- DB API
- Relational API
- Function API
- Types API
- Expression API
- Spark API
- API Reference
- Known Python Issues
- R
- Rust
- Swift
- Wasm
- SQL
- Introduction
- Statements
- Overview
- ANALYZE
- ALTER TABLE
- ALTER VIEW
- ATTACH and DETACH
- CALL
- CHECKPOINT
- COMMENT ON
- COPY
- CREATE INDEX
- CREATE MACRO
- CREATE SCHEMA
- CREATE SECRET
- CREATE SEQUENCE
- CREATE TABLE
- CREATE VIEW
- CREATE TYPE
- DELETE
- DESCRIBE
- DROP
- EXPORT and IMPORT DATABASE
- INSERT
- LOAD / INSTALL
- PIVOT
- Profiling
- SELECT
- SET / RESET
- SET VARIABLE
- SUMMARIZE
- Transaction Management
- UNPIVOT
- UPDATE
- USE
- VACUUM
- Query Syntax
- SELECT
- FROM and JOIN
- WHERE
- GROUP BY
- GROUPING SETS
- HAVING
- ORDER BY
- LIMIT and OFFSET
- SAMPLE
- Unnesting
- WITH
- WINDOW
- QUALIFY
- VALUES
- FILTER
- Set Operations
- Prepared Statements
- Data Types
- Overview
- Array
- Bitstring
- Blob
- Boolean
- Date
- Enum
- Interval
- List
- Literal Types
- Map
- NULL Values
- Numeric
- Struct
- Text
- Time
- Timestamp
- Time Zones
- Union
- Typecasting
- Expressions
- Overview
- CASE Expression
- Casting
- Collations
- Comparisons
- IN Operator
- Logical Operators
- Star Expression
- Subqueries
- TRY
- Functions
- Overview
- Aggregate Functions
- Array Functions
- Bitstring Functions
- Blob Functions
- Date Format Functions
- Date Functions
- Date Part Functions
- Enum Functions
- Interval Functions
- Lambda Functions
- List Functions
- Map Functions
- Nested Functions
- Numeric Functions
- Pattern Matching
- Regular Expressions
- Struct Functions
- Text Functions
- Time Functions
- Timestamp Functions
- Timestamp with Time Zone Functions
- Union Functions
- Utility Functions
- Window Functions
- Constraints
- Indexes
- Meta Queries
- DuckDB's SQL Dialect
- Overview
- Indexing
- Friendly SQL
- Keywords and Identifiers
- Order Preservation
- PostgreSQL Compatibility
- SQL Quirks
- Samples
- Configuration
- Extensions
- Overview
- Installing Extensions
- Advanced Installation Methods
- Distributing Extensions
- Versioning of Extensions
- Troubleshooting of Extensions
- Core Extensions
- Overview
- AutoComplete
- Avro
- AWS
- Azure
- Delta
- DuckLake
- Encodings
- Excel
- Full Text Search
- httpfs (HTTP and S3)
- Iceberg
- Overview
- Iceberg REST Catalogs
- Amazon S3 Tables
- Amazon SageMaker Lakehouse (AWS Glue)
- Troubleshooting
- ICU
- inet
- jemalloc
- MySQL
- PostgreSQL
- Spatial
- SQLite
- TPC-DS
- TPC-H
- UI
- VSS
- Guides
- Overview
- Data Viewers
- Database Integration
- File Formats
- Overview
- CSV Import
- CSV Export
- Directly Reading Files
- Excel Import
- Excel Export
- JSON Import
- JSON Export
- Parquet Import
- Parquet Export
- Querying Parquet Files
- File Access with the file: Protocol
- Network and Cloud Storage
- Overview
- HTTP Parquet Import
- S3 Parquet Import
- S3 Parquet Export
- S3 Iceberg Import
- S3 Express One
- GCS Import
- Cloudflare R2 Import
- DuckDB over HTTPS / S3
- Fastly Object Storage Import
- Meta Queries
- Describe Table
- EXPLAIN: Inspect Query Plans
- EXPLAIN ANALYZE: Profile Queries
- List Tables
- Summarize
- DuckDB Environment
- ODBC
- Performance
- Overview
- Environment
- Import
- Schema
- Indexing
- Join Operations
- File Formats
- How to Tune Workloads
- My Workload Is Slow
- Benchmarks
- Working with Huge Databases
- Python
- Installation
- Executing SQL
- Jupyter Notebooks
- marimo Notebooks
- SQL on Pandas
- Import from Pandas
- Export to Pandas
- Import from Numpy
- Export to Numpy
- SQL on Arrow
- Import from Arrow
- Export to Arrow
- Relational API on Pandas
- Multiple Python Threads
- Integration with Ibis
- Integration with Polars
- Using fsspec Filesystems
- SQL Editors
- SQL Features
- Snippets
- Creating Synthetic Data
- Dutch Railway Datasets
- Sharing Macros
- Analyzing a Git Repository
- Importing Duckbox Tables
- Copying an In-Memory Database to a File
- Troubleshooting
- Glossary of Terms
- Browsing Offline
- Operations Manual
- Overview
- DuckDB's Footprint
- Logging
- Securing DuckDB
- Non-Deterministic Behavior
- Limits
- Development
- DuckDB Repositories
- Profiling
- Building DuckDB
- Overview
- Build Configuration
- Building Extensions
- Android
- Linux
- macOS
- Raspberry Pi
- Windows
- Python
- R
- Troubleshooting
- Unofficial and Unsupported Platforms
- Benchmark Suite
- Testing
- Internals
- Sitemap
- Live Demo
DuckDB 1.3 ドキュメント 全文検索
Results of 1 - 1 of about 1 for fruit (0.001 sec.)
- Integration with Polars – DuckDB 9414
- This page is for DuckDB 1.3, which is outdated. Switch to the current version . Search Shortcut cmd + k | ctrl + k Installation Documentation Getting Started Connect Overview Concurrency Data Import Overview Data Sources CSV Files Overview
...s they exist in the current scope. import duckdb import polars as pl df = pl . DataFrame ( { "A" : [ 1 , 2 , 3 , 4 , 5 ], "fruits" : [ "banana" , "banana" , "apple" , "apple" , "banana" ], "B" : [ 5 , 4 , 3 , 2 , 1 ], "cars" : [ "beetle" , "audi" , "b...results as Polars DataFrames using the .pl() result-conversion method. df = duckdb . sql ( """ SELECT 1 AS id, 'banana' AS fruit UNION ALL SELECT 2, 'apple' UNION ALL SELECT 3, 'mango'""" ). pl () print ( df ) shape: (3, 2) ┌─────┬────────┐ │ id ┆ fru...rs DataFrames DuckDB banana duckdb apple beetle library Apache Arrow query results using integration pyarrow polars import fruit mango Documentation Guides Copy Markdown Integration built 関連するページ SQL on Pandas SQL on Apache Arrow Import from Ap... - https://man.mtool.work/duckdb/1.3/guides/python/polars.html
PREV
1
NEXT
DuckDB 1.3 Documentation / man.mtool.work